Research

Gender-based affirmative action policies in top-ranked STEM institutions aim to enhance women's representation in both higher education and the labor force. While these policies can promote diversity, they may also increase statistical discrimination in hiring practices as colleges lower admission standards to increase female enrollment. This paper examines this trade-off and investigates how expanding seats for women in premier Indian engineering colleges affects gender discrimination in hiring. I conduct a large-scale correspondence study that randomizes gender, college type, and year of entry and induces variation in policy exposure within the experimental design. The results indicate no significant male-female callback gap at top colleges before or after the policy; however, women from lower-ranked colleges face disadvantages. Specifically, the policy implementation led to a 52% drop in the female callback probability, increasing male-female callback gap by 2 percentage points in these colleges. To further shed light on actual employment outcomes, I analyze data scraped from LinkedIn profiles, revealing consistent evidence that supports my findings. I propose a model of statistical discrimination that incorporates affirmative action for women at top colleges, aligning with the observed trends in hiring practices.

Presentations:

Midwest International Economic Development Conference (MWIEDC) 2025, University of Illinois Urbana-Champaign
Pacific Area Conference in Development Economics (PacDev) 2025, University of Southern California

Southern Economic Association (SEA) 2024, Washington DC
North East Universities Development Consortium (NEUDC) 2024, Northeastern University
Washington Area Development Economics Symposium (WADES) 2024, Georgetown University

Women are largely underrepresented in STEM careers associated with higher labor market returns. This gender gap is even more stark in a context where societal biases are prevalent and female role models are lacking. This paper investigates the impact of an affirmative action policy implemented in an elite educational institution in India that ensures additional seats specifically for women in undergraduate STEM courses. After the policy was implemented, the proportion of women enrolling increased by 100%, proportion of women taking the college entrance exam increased by 10% and those qualifying the exam increased by 15%. Using nationally representative data, I employ a triple difference strategy and find a 27% increase in the probability of studying science courses after Grade 10 amongst younger girls exposed to this policy, suggesting a 6% increase in the expected earnings of women. 

Presentations:
18th Annual Conference on Economic Growth & Development (ACEGD) 2023, ISI Delhi
Huskey Graduate Research Exhibition 2022, University of Virginia
Econ Talk Seminar 2021, IIT Delhi

We deliver a theoretical model of domestic violence which proposes that delayed age of marriage aids women in complying to socially desirable behavior expected by the husband rather than challenging the dis-empowering norms. The theory predicts that delaying the age of marriage would reduce domestic violence, but individual wealth of the wife would offset this effect. We corroborate the model by leveraging two rounds of nationally representative health surveys from India and differences in societal and marriage practices among Hindus and Muslims, finding causal empirical support for our theory. Using age of menarche as an instrument, we find that one year delay in age of marriage reduces emotional violence by 18%, less severe physical violence by 26% and severe physical violence by 39%. These findings are stronger amongst Hindu women and gets muted for Muslims who typically have higher wealth at the time of marriage. Our paper highlights that fear of violence can undermine empowering policies when there is widespread acceptance of beating social norms.